In the course notebook:
training_datagen = ImageDataGenerator(
rescale = 1./255,
rotation_range=40,
width_shift_range=0.2,
height_shift_range=0.2,
shear_range=0.2,
zoom_range=0.2,
horizontal_flip=True,
fill_mode='nearest')
However, in the rock-paper-scissors data set, shear is bad.
Removing this argument dramatically improves val_loss.
It looks like it could be corrected on that point.